Predictive modeling of the outcomes of chemotherapyinduced (febrile) neutropenia prophylaxis with biosimilar filgrastim (MONITOR-GCSF study)

M. Aapro, H. Ludwig, C. Bokemeyer, P. Gascón, M. Boccadoro, K. Denhaerynck, A. Krendyukov, M. Gorray, K. MacDonald, I. Abraham

Research output: Contribution to journalArticle

18 Scopus citations

Abstract

Background: Risk models of chemotherapy-induced (CIN) and febrile neutropenia (FN) have to date focused on determinants measured at the start of chemotherapy. We extended this static approach with a dynamic approach of CIN/FN risk modeling at the start of each cycle. Design: We applied predictive modeling using multivariate logistic regression to identify determinants of CIN/FN episodes and related hospitalizations and chemotherapy disturbances (CIN/FN consequences) in analyses at the patient ('ever' during the whole period of chemotherapy) and cycle-level (during a given chemotherapy cycle). Statistical dependence of cycle data being 'nested' under patients was managed using generalized estimation equations. Predictive performance of each model was evaluated using bootstrapped c concordance statistics. Results: Static patient-level risk models of 'ever' experiencing CIN/FN adverse events and consequences during a planned chemotherapy regimen included predictors related to history, risk factors, and prophylaxis initiation and intensity. Dynamic cycle-level risk models of experiencing CIN/FN adverse events and consequences in an upcoming cycle included predictors related to history, risk factors, and prophylaxis initiation and intensity; as well as prophylaxis duration, CIN/FN in prior cycle, and treatment center characteristics. Conclusion(s): These 'real-world evidence' models provide clinicians with the ability to anticipate CIN/FN adverse events and their consequences at the start of a chemotherapy line (static models); and, innovatively, to assess risk of CIN/ FN adverse events and their consequences at the start of each cycle (dynamic models). This enables individualized patient treatment and is consistent with the EORTC recommendation to re-appraise CIN/FN risk at the start of each cycle. Prophylaxis intensity (under-, correctly-, or over-prophylacted relative to current EORTC guidelines) is a major determinant. Under-prophylaxis is clinically unsafe. Over-prophylaxis of patients administered chemotherapy with intermediate or low myelotoxicity levels may be beneficial, both in patients with and without risk factors, and must be validated in future studies.

Original languageEnglish (US)
Pages (from-to)2039-2045
Number of pages7
JournalAnnals of Oncology
Volume27
Issue number11
DOIs
StatePublished - Jan 1 2016

Keywords

  • Biosimilar
  • Chemotherapy-induced neutropenia
  • Febrile neutropenia
  • Filgrastim
  • Granulocyte colony-stimulating factor
  • Modeling

ASJC Scopus subject areas

  • Hematology
  • Oncology

Fingerprint Dive into the research topics of 'Predictive modeling of the outcomes of chemotherapyinduced (febrile) neutropenia prophylaxis with biosimilar filgrastim (MONITOR-GCSF study)'. Together they form a unique fingerprint.

  • Cite this

    Aapro, M., Ludwig, H., Bokemeyer, C., Gascón, P., Boccadoro, M., Denhaerynck, K., Krendyukov, A., Gorray, M., MacDonald, K., & Abraham, I. (2016). Predictive modeling of the outcomes of chemotherapyinduced (febrile) neutropenia prophylaxis with biosimilar filgrastim (MONITOR-GCSF study). Annals of Oncology, 27(11), 2039-2045. https://doi.org/10.1093/annonc/mdw309